TY - GEN
T1 - Multiscale modelling of multifunctional composites
T2 - ASME 2021 International Mechanical Engineering Congress and Exposition, IMECE 2021
AU - Babu, Sandeep Suresh
AU - Mourad, Abdel Hamid I.
N1 - Publisher Copyright:
Copyright © 2021 by ASME
PY - 2021
Y1 - 2021
N2 - Multi-scale modelling is a cornerstone for the relatively new class of hierarchical materials which can perform multifunctional tasks, owing to their electrical, magnetic or thermal properties. Careful design strategies are to be devised, in-order to maintain their multi-functionality over the expected range of operation. In this study, we focus on these materials, which can be manufactured using a specialized technique of additive manufacturing, known as fused deposition modelling (FDM), owing to its flexibility and compatibility, working with polymer based materials. A review has been made on the various parameters affecting the manufacturing process, and how these variations can affect the properties of the end product. Future research directions are also pointed out, including stimuli responsive printing technique, popularly known as 4D printing and integration of neural networks into the manufacturing process which can improve the overall design lifecycle efficiency. This can involve autonomous production of test specimen, and revert back the data for model improvement, thereby enhancing predictive capabilities. The major focus of this work is on how we can use our current knowledge and techniques in the design of efficient and effective multifunctional composite materials from the bottoms-up approach.
AB - Multi-scale modelling is a cornerstone for the relatively new class of hierarchical materials which can perform multifunctional tasks, owing to their electrical, magnetic or thermal properties. Careful design strategies are to be devised, in-order to maintain their multi-functionality over the expected range of operation. In this study, we focus on these materials, which can be manufactured using a specialized technique of additive manufacturing, known as fused deposition modelling (FDM), owing to its flexibility and compatibility, working with polymer based materials. A review has been made on the various parameters affecting the manufacturing process, and how these variations can affect the properties of the end product. Future research directions are also pointed out, including stimuli responsive printing technique, popularly known as 4D printing and integration of neural networks into the manufacturing process which can improve the overall design lifecycle efficiency. This can involve autonomous production of test specimen, and revert back the data for model improvement, thereby enhancing predictive capabilities. The major focus of this work is on how we can use our current knowledge and techniques in the design of efficient and effective multifunctional composite materials from the bottoms-up approach.
KW - Fused deposition modelling
KW - Multiscale modelling
KW - Review
UR - http://www.scopus.com/inward/record.url?scp=85124509751&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85124509751&partnerID=8YFLogxK
U2 - 10.1115/IMECE2021-73276
DO - 10.1115/IMECE2021-73276
M3 - Conference contribution
AN - SCOPUS:85124509751
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
BT - Advanced Materials
PB - American Society of Mechanical Engineers (ASME)
Y2 - 1 November 2021 through 5 November 2021
ER -